To study and develop the mathematical models to review the properties of synovial fluids

Crepitus vibrational and acoustic signal analysis of the human facet joints of the lumbar spine has historically been a difficult problem due to the inhomogeneous and varied signal characteristics. Here we improve upon our previous automated computational method, now enhancing it for analysis of human crepitus. Compared with this group's previous studies using a mechanical model; human crepitus is extremely complex. Moreover, there is no existing availability of large numbers of human crepitus data to enable effective machine learning approaches. Therefore, we proposed an automated method (AM) of analysis that, analogous to machine learning, used a test set (n = 16) and an experimental set of data (n = 48). The advantage of beginning with this approach was that we identified characteristics of the signal that are unavailable or otherwise not easily obtained in more advanced methods, such as “black box” machine learning methods. However, we did not have the high fidelity that a machine learning approach would provide. This was shown by only a fair level of inter-rater agreement (Kw = 0.367; SE = 0.054, 95% CI = 0.260-0.474) between the AM and human observers before adjustments were made in the AM. Following adjustments to the AM, inter-rater agreement improved to a substantial level of agreement (Kw = 0.788; SE = 0.056, 95% CI = 0.0.682-0.895). In the future, we recommend a machine learning study with a high number of subjects, that can better capture the nuances of varying types of human crepitus.

show abstract

Automated Vibration and Acoustic Crepitus Sensing in Humans

Roytman

Faydenko

Budavich

et al. 2023

Journal of Tribology

View full text Add to dashboard Cite

show abstract

Rheological behavior of the synovial fluid: a mathematical challenge

Ouerfelli,

Vrinceanu,

Mliki

et al. 2024

Front. Mater.

View full text Add to dashboard Cite

BackgroundSynovial fluid (SF) is often used for diagnostic and research purposes as it reflects the local inflammatory environment. Owing to its complex composition, especially the presence of hyaluronic acid, SF is usually viscous and non-homogeneous. The presence of high-molar-mass hyaluronan in this fluid gives it the required viscosity for its function as a lubricant. Viscosity is the greatest major hydraulic attribute of the SF in articular cartilage.MethodsEmpirical modeling of previously published results was performed. In this study, we explored the flow of a non-Newtonian fluid that could be used to model the SF flow. Analyzing the flow in a simple geometry can help explain the model’s efficacy and assess the SF models. By employing some viscosity data reported elsewhere, we summarized the dynamic viscosity values of normal human SF of the knee joints in terms of time after injecting hyaluronidase (HYAL) at 25°C. The suggested quadratic behavior was obtained through extrapolation. For accurate diagnosis or prediction, the comparison between three specific parameters (ai, t0, and ln η0) was made for normal and pathological cases under the same experimental conditions for treatment by addition of HYAL and for investigation of the rheological properties. A new model on the variation of viscosity on the SF of knee joints with time after injection of HYAL with respect to normal and postmortem samples at different velocity gradients was proposed using data previously reported elsewhere.ResultsThe rheological behavior of SF changes progressively over time from non-Newtonian to a Newtonian profile, where the viscosity has a limiting constant value (η0) independent of the gradient velocity at a unique characteristic time (t0 ≈ 8.5 h). The proposed three-parameter model with physical meaning offers insights into future pathological cases. The outcomes of this work are expected to offer new perspectives for diagnosis, criteria, and prediction of pathological case types through comparisons with new parameter values treated under the same experimental conditions as HYAL injection. This study also highlights the importance of HYAL treatment for better intra-assay precision.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

To study and develop the mathematical models to review the properties of synovial fluids

Cited by 2 publications

References 17 publications

Automated Vibration and Acoustic Crepitus Sensing in Humans

Automated Vibration and Acoustic Crepitus Sensing in Humans

Rheological behavior of the synovial fluid: a mathematical challenge

Contact Info

Product

Resources

About